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fixed error message for incorrect varname being passed through climat…
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…epy_filter(), added test for wrong variable names raising a ValueError
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@anguswg-ucsb
anguswg-ucsb committed May 7, 2024
1 parent 0d0bbab commit af9b114
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Showing 2 changed files with 136 additions and 125 deletions.
10 changes: 8 additions & 2 deletions climatePy/_climatepy_filter.py
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Original file line number Diff line number Diff line change
Expand Up @@ -210,8 +210,14 @@ def climatepy_filter(
else:
bad = list(set(varname) - set(u))
m = catalog[['variable', 'description', 'units']].drop_duplicates()
message = f"'{bad}' not avaliable parameter for '{catalog.iloc[0]['id']}'. Try: \n\t{'> ' + m['variable'] + ' [' + m['units'] + '] (' + m['description'] + ')' }"
raise Exception(message)
suggested_vals = list(zip(m['variable'].tolist(), m['description'].tolist(), m['units'].tolist()))
suggested_strs = "\n\t> " + "\n\t> ".join([f"{i[0]} [{i[2]}] ({i[1]})" for i in suggested_vals])
message = f"'{bad}' not avaliable parameter for '{catalog.iloc[0]['id']}'. Try: {suggested_strs}"

# message = f"'{bad}' not avaliable parameter for '{catalog.iloc[0]['id']}'. Try: \n\t{'> ' + m['variable'] + ' [' + m['units'] + '] (' + m['description'] + ')' }"
# message = f"'{bad}' not avaliable parameter for '{catalog.iloc[0]['id']}'. Try: \n\t{'> ' + str(m['variable']) + ' [' + str(m['units']) + '] (' + str(m['description']) + ')' }"

raise ValueError(message)

# 2. scenario filter
if scenario is not None:
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251 changes: 128 additions & 123 deletions tests/test_shortcuts.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,6 +10,7 @@
# import climatePy._dap as climatePy
import climatePy._shortcuts as climatePy
# import climatePy._climatepy_filter as climatePy
# import climatePy

# data manipulation libs
import pandas as pd
Expand Down Expand Up @@ -237,7 +238,11 @@ def test_getGridMET_case4(AOI):
assert "rmin" in output["rmin"].time[0].values.item()
assert len(output["rmin"].time.values) == 1827


def test_getGridMET_value_error_with_incorrect_varname(AOI):

with pytest.raises(ValueError):
climatePy.getGridMET(AOI, "prcp", "2010-01-01", "2010-02-01", verbose=True)

def test_getTerraClimNormals_case1(AOI):

# ---- Case 1 ----
Expand Down Expand Up @@ -1125,169 +1130,169 @@ def test_getISRIC_soils_case3(AOI):
# assert output['Vertisols'].shape == (432, 945)
# assert output['Gypsisols'].shape == (432, 945)

# # def test_getCHIRPS_case1(AOI):
# def test_getCHIRPS_case1(AOI):

# # # ---- Case 1: Single month CHIRPS ----
# # verbose = True
# # startDate = "2019-01-01"
# # endDate = "2019-01-01"
# # varname = 'precip'
# # timeRes = "daily"
# # ---- Case 1: Single month CHIRPS ----
# verbose = True
# startDate = "2019-01-01"
# endDate = "2019-01-01"
# varname = 'precip'
# timeRes = "daily"

# # # NOTE: CHIRPS data is currently inaccesible due to server issues with the data provider
# # # NOTE: This test will fail until the data provider resolves the server issues
# # with pytest.raises(Exception):
# # # Call function to get output
# # output = climatePy.getCHIRPS(AOI, varname, startDate, endDate, timeRes, verbose)
# # NOTE: CHIRPS data is currently inaccesible due to server issues with the data provider
# # NOTE: This test will fail until the data provider resolves the server issues
# with pytest.raises(Exception):
# # Call function to get output
# output = climatePy.getCHIRPS(AOI, varname, startDate, endDate, timeRes, verbose)

# # # # Assert that the output is a dictionary
# # # assert type(output) == dict
# # # Assert that the output is a dictionary
# # assert type(output) == dict

# # # # Assert that the output dictionary has the correct keys
# # # assert set(output.keys()) == {"precip"}
# # # Assert that the output dictionary has the correct keys
# # assert set(output.keys()) == {"precip"}

# # # # Assert that the values of the output dictionary are xarray DataArrays
# # # assert isinstance(output["precip"], xr.DataArray)
# # # Assert that the values of the output dictionary are xarray DataArrays
# # assert isinstance(output["precip"], xr.DataArray)

# # # # Assert that the dimensions of the output DataArrays are correct
# # # assert output["precip"].dims == ("y", "x", "time")
# # # Assert that the dimensions of the output DataArrays are correct
# # assert output["precip"].dims == ("y", "x", "time")

# # # # Assert that the temporal resolution of the output DataArrays is correct
# # # start_date1 = datetime.strptime(re.search(r'\d{4}-\d{2}-\d{2}', output["precip"].time[0].values.item()).group(0), "%Y-%m-%d")
# # # end_date1 = datetime.strptime(re.search(r'\d{4}-\d{2}-\d{2}', output["precip"].time[-1].values.item()).group(0), "%Y-%m-%d")
# # # Assert that the temporal resolution of the output DataArrays is correct
# # start_date1 = datetime.strptime(re.search(r'\d{4}-\d{2}-\d{2}', output["precip"].time[0].values.item()).group(0), "%Y-%m-%d")
# # end_date1 = datetime.strptime(re.search(r'\d{4}-\d{2}-\d{2}', output["precip"].time[-1].values.item()).group(0), "%Y-%m-%d")

# # # # check temporal range
# # # assert end_date1 - start_date1 == pd.Timedelta("0D")
# # # check temporal range
# # assert end_date1 - start_date1 == pd.Timedelta("0D")

# # # assert "precip" in output["precip"].time[0].values.item()
# # assert "precip" in output["precip"].time[0].values.item()

# # # assert len(output["precip"].time.values) == 1
# # # assert output['precip'].shape == (19, 40, 1)
# # assert len(output["precip"].time.values) == 1
# # assert output['precip'].shape == (19, 40, 1)

# # def test_getCHIRPS_case2(AOI):
# # # ---- Case 2: Multi Month CHIRPS ----
# # verbose = True
# # startDate = "2019-01-01"
# # endDate = "2019-03-01"
# # varname = 'precip'
# # timeRes = "daily"
# def test_getCHIRPS_case2(AOI):
# # ---- Case 2: Multi Month CHIRPS ----
# verbose = True
# startDate = "2019-01-01"
# endDate = "2019-03-01"
# varname = 'precip'
# timeRes = "daily"

# # # NOTE: CHIRPS data is currently inaccesible due to server issues with the data provider
# # # NOTE: This test will fail until the data provider resolves the server issues
# # with pytest.raises(Exception):
# # # Call function to get output
# # output = climatePy.getCHIRPS(AOI, varname, startDate, endDate, timeRes, verbose)
# # print(f"----- CHIRPS test case 2 keys: \n > {output.keys()} ----")
# # NOTE: CHIRPS data is currently inaccesible due to server issues with the data provider
# # NOTE: This test will fail until the data provider resolves the server issues
# with pytest.raises(Exception):
# # Call function to get output
# output = climatePy.getCHIRPS(AOI, varname, startDate, endDate, timeRes, verbose)
# print(f"----- CHIRPS test case 2 keys: \n > {output.keys()} ----")

# # # assert type(output) == dict
# # assert type(output) == dict

# # # # Assert that the output dictionary has the correct keys
# # # assert set(output.keys()) == {"precip"}
# # # Assert that the output dictionary has the correct keys
# # assert set(output.keys()) == {"precip"}

# # # # Assert that the values of the output dictionary are xarray DataArrays
# # # assert isinstance(output["precip"], xr.DataArray)
# # # Assert that the values of the output dictionary are xarray DataArrays
# # assert isinstance(output["precip"], xr.DataArray)

# # # # Assert that the dimensions of the output DataArrays are correct
# # # assert output["precip"].dims == ("y", "x", "time")
# # # Assert that the dimensions of the output DataArrays are correct
# # assert output["precip"].dims == ("y", "x", "time")

# # # # Assert that the temporal resolution of the output DataArrays is correct
# # # start_date1 = datetime.strptime(re.search(r'\d{4}-\d{2}-\d{2}', output["precip"].time[0].values.item()).group(0), "%Y-%m-%d")
# # # end_date1 = datetime.strptime(re.search(r'\d{4}-\d{2}-\d{2}', output["precip"].time[-1].values.item()).group(0), "%Y-%m-%d")
# # # Assert that the temporal resolution of the output DataArrays is correct
# # start_date1 = datetime.strptime(re.search(r'\d{4}-\d{2}-\d{2}', output["precip"].time[0].values.item()).group(0), "%Y-%m-%d")
# # end_date1 = datetime.strptime(re.search(r'\d{4}-\d{2}-\d{2}', output["precip"].time[-1].values.item()).group(0), "%Y-%m-%d")

# # # # check temporal range
# # # assert end_date1 - start_date1 == pd.Timedelta("59D")
# # # check temporal range
# # assert end_date1 - start_date1 == pd.Timedelta("59D")

# # # assert "precip" in output["precip"].time[0].values.item()
# # assert "precip" in output["precip"].time[0].values.item()

# # # assert len(output["precip"].time.values) == 3
# # # assert output['precip'].shape == (19, 40, 3)
# # assert len(output["precip"].time.values) == 3
# # assert output['precip'].shape == (19, 40, 3)


# # def test_getCHIRPS_case3(AOI):
# # # ---- Case 3: Multi Year Month CHIRPS ----
# # verbose = True
# # startDate = "2019-01-01"
# # endDate = "2019-01-15"
# # varname = 'precip'
# # timeRes = "daily"
# def test_getCHIRPS_case3(AOI):
# # ---- Case 3: Multi Year Month CHIRPS ----
# verbose = True
# startDate = "2019-01-01"
# endDate = "2019-01-15"
# varname = 'precip'
# timeRes = "daily"

# # # NOTE: CHIRPS data is currently inaccesible due to server issues with the data provider
# # # NOTE: This test will fail until the data provider resolves the server issues
# # with pytest.raises(Exception):
# # # Call function to get output
# # output = climatePy.getCHIRPS(AOI, varname, startDate, endDate, timeRes, verbose)
# # NOTE: CHIRPS data is currently inaccesible due to server issues with the data provider
# # NOTE: This test will fail until the data provider resolves the server issues
# with pytest.raises(Exception):
# # Call function to get output
# output = climatePy.getCHIRPS(AOI, varname, startDate, endDate, timeRes, verbose)

# # print(f"----- CHIRPS test case 3 keys: \n > {output.keys()} ----")
# print(f"----- CHIRPS test case 3 keys: \n > {output.keys()} ----")

# # # # Assert that the output is a dictionary
# # # assert type(output) == dict
# # # Assert that the output is a dictionary
# # assert type(output) == dict

# # # # Assert that the output dictionary has the correct keys
# # # assert set(output.keys()) == {"precip"}
# # # Assert that the output dictionary has the correct keys
# # assert set(output.keys()) == {"precip"}

# # # # Assert that the values of the output dictionary are xarray DataArrays
# # # assert isinstance(output["precip"], xr.DataArray)
# # # Assert that the values of the output dictionary are xarray DataArrays
# # assert isinstance(output["precip"], xr.DataArray)

# # # # Assert that the dimensions of the output DataArrays are correct
# # # assert output["precip"].dims == ("y", "x", "time")
# # # Assert that the dimensions of the output DataArrays are correct
# # assert output["precip"].dims == ("y", "x", "time")

# # # # Assert that the temporal resolution of the output DataArrays is correct
# # # start_date1 = datetime.strptime(re.search(r'\d{4}-\d{2}-\d{2}',
# # # output["precip"].time[0].values.item()).group(0), "%Y-%m-%d")
# # # Assert that the temporal resolution of the output DataArrays is correct
# # start_date1 = datetime.strptime(re.search(r'\d{4}-\d{2}-\d{2}',
# # output["precip"].time[0].values.item()).group(0), "%Y-%m-%d")

# # # end_date1 = datetime.strptime(re.search(r'\d{4}-\d{2}-\d{2}',
# # # output["precip"].time[-1].values.item()).group(0), "%Y-%m-%d")
# # end_date1 = datetime.strptime(re.search(r'\d{4}-\d{2}-\d{2}',
# # output["precip"].time[-1].values.item()).group(0), "%Y-%m-%d")

# # # # check temporal range
# # # assert end_date1 - start_date1 == pd.Timedelta("15D")
# # # check temporal range
# # assert end_date1 - start_date1 == pd.Timedelta("15D")

# # # assert "precip" in output["precip"].time[0].values.item()
# # assert "precip" in output["precip"].time[0].values.item()

# # # assert len(output["precip"].time.values) == 14
# # # assert output['precip'].shape == (19, 40, 14)
# # assert len(output["precip"].time.values) == 14
# # assert output['precip'].shape == (19, 40, 14)

# # def test_getCHIRPS_case4(AOI):
# # # ---- Case 4: Monthly Multi Year CHIRPS ----
# # verbose = True
# # startDate = "2019-01-01"
# # endDate = "2020-02-01"
# # varname = 'precip'
# # timeRes = "monthly"
# def test_getCHIRPS_case4(AOI):
# # ---- Case 4: Monthly Multi Year CHIRPS ----
# verbose = True
# startDate = "2019-01-01"
# endDate = "2020-02-01"
# varname = 'precip'
# timeRes = "monthly"

# # # NOTE: CHIRPS data is currently inaccesible due to server issues with the data provider
# # # NOTE: This test will fail until the data provider resolves the server issues
# # with pytest.raises(Exception):
# # # Call function to get output
# # output = climatePy.getCHIRPS(AOI, varname, startDate, endDate, timeRes, verbose)
# # NOTE: CHIRPS data is currently inaccesible due to server issues with the data provider
# # NOTE: This test will fail until the data provider resolves the server issues
# with pytest.raises(Exception):
# # Call function to get output
# output = climatePy.getCHIRPS(AOI, varname, startDate, endDate, timeRes, verbose)

# # # # Assert that the output is a dictionary
# # # assert type(output) == dict
# # # Assert that the output is a dictionary
# # assert type(output) == dict

# # # # Assert that the output dictionary has the correct keys
# # # assert set(output.keys()) == {"precip"}
# # # Assert that the output dictionary has the correct keys
# # assert set(output.keys()) == {"precip"}

# # # # Assert that the values of the output dictionary are xarray DataArrays
# # # assert isinstance(output["precip"], xr.DataArray)
# # # Assert that the values of the output dictionary are xarray DataArrays
# # assert isinstance(output["precip"], xr.DataArray)

# # # # Assert that the dimensions of the output DataArrays are correct
# # # assert output["precip"].dims == ("y", "x", "time")
# # # Assert that the dimensions of the output DataArrays are correct
# # assert output["precip"].dims == ("y", "x", "time")

# # # # Assert that the temporal resolution of the output DataArrays is correct
# # # start_date1 = datetime.strptime(re.search(r'\d{4}-\d{2}-\d{2}',
# # # output["precip"].time[0].values.item()).group(0), "%Y-%m-%d")
# # # Assert that the temporal resolution of the output DataArrays is correct
# # start_date1 = datetime.strptime(re.search(r'\d{4}-\d{2}-\d{2}',
# # output["precip"].time[0].values.item()).group(0), "%Y-%m-%d")

# # # end_date1 = datetime.strptime(re.search(r'\d{4}-\d{2}-\d{2}',
# # # output["precip"].time[-1].values.item()).group(0), "%Y-%m-%d")
# # end_date1 = datetime.strptime(re.search(r'\d{4}-\d{2}-\d{2}',
# # output["precip"].time[-1].values.item()).group(0), "%Y-%m-%d")

# # # # check temporal range
# # # assert end_date1 - start_date1 == pd.Timedelta("396D")
# # # assert "precip" in output["precip"].time[0].values.item()
# # # check temporal range
# # assert end_date1 - start_date1 == pd.Timedelta("396D")
# # assert "precip" in output["precip"].time[0].values.item()

# # # # calculate number of months
# # # months = (end_date1.year - start_date1.year) * 12 + end_date1.month - start_date1.month
# # # months = months + 1 if end_date1.day >= end_date1.day else months
# # # calculate number of months
# # months = (end_date1.year - start_date1.year) * 12 + end_date1.month - start_date1.month
# # months = months + 1 if end_date1.day >= end_date1.day else months

# # # # check that number of months in output is correct (within 1 month)
# # # assert (len(output["precip"]['time']) == months or
# # # len(output["precip"]['time']) + 1 == months or
# # # len(output["precip"]['time']) - 1 == months)
# # # check that number of months in output is correct (within 1 month)
# # assert (len(output["precip"]['time']) == months or
# # len(output["precip"]['time']) + 1 == months or
# # len(output["precip"]['time']) - 1 == months)

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